Overview

Dataset statistics

Number of variables15
Number of observations1080
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory126.7 KiB
Average record size in memory120.1 B

Variable types

Numeric15

Warnings

gross-margin is highly correlated with pre-tax-profit-marginHigh correlation
operating-margin is highly correlated with ebit-margin and 4 other fieldsHigh correlation
ebit-margin is highly correlated with operating-margin and 4 other fieldsHigh correlation
pre-tax-profit-margin is highly correlated with gross-margin and 5 other fieldsHigh correlation
net-profit-margin is highly correlated with operating-margin and 4 other fieldsHigh correlation
asset-turnover is highly correlated with receiveable-turnoverHigh correlation
receiveable-turnover is highly correlated with asset-turnoverHigh correlation
days-sales-in-receivables is highly correlated with book-value-per-shareHigh correlation
roa is highly correlated with operating-margin and 4 other fieldsHigh correlation
roi is highly correlated with operating-margin and 4 other fieldsHigh correlation
book-value-per-share is highly correlated with days-sales-in-receivablesHigh correlation
gross-margin is highly correlated with operating-margin and 3 other fieldsHigh correlation
operating-margin is highly correlated with gross-margin and 5 other fieldsHigh correlation
ebit-margin is highly correlated with gross-margin and 5 other fieldsHigh correlation
pre-tax-profit-margin is highly correlated with gross-margin and 6 other fieldsHigh correlation
net-profit-margin is highly correlated with gross-margin and 5 other fieldsHigh correlation
asset-turnover is highly correlated with operating-margin and 2 other fieldsHigh correlation
receiveable-turnover is highly correlated with days-sales-in-receivablesHigh correlation
days-sales-in-receivables is highly correlated with receiveable-turnoverHigh correlation
roe is highly correlated with roa and 1 other fieldsHigh correlation
roa is highly correlated with operating-margin and 5 other fieldsHigh correlation
roi is highly correlated with pre-tax-profit-margin and 3 other fieldsHigh correlation
gross-margin is highly correlated with operating-margin and 1 other fieldsHigh correlation
operating-margin is highly correlated with gross-margin and 3 other fieldsHigh correlation
ebit-margin is highly correlated with operating-margin and 2 other fieldsHigh correlation
pre-tax-profit-margin is highly correlated with gross-margin and 3 other fieldsHigh correlation
net-profit-margin is highly correlated with operating-margin and 3 other fieldsHigh correlation
receiveable-turnover is highly correlated with days-sales-in-receivablesHigh correlation
days-sales-in-receivables is highly correlated with receiveable-turnoverHigh correlation
roe is highly correlated with roa and 1 other fieldsHigh correlation
roa is highly correlated with net-profit-margin and 2 other fieldsHigh correlation
roi is highly correlated with roe and 1 other fieldsHigh correlation
pre-tax-profit-margin is highly correlated with ebit-margin and 5 other fieldsHigh correlation
ebit-margin is highly correlated with pre-tax-profit-margin and 5 other fieldsHigh correlation
receiveable-turnover is highly correlated with gross-margin and 1 other fieldsHigh correlation
roa is highly correlated with pre-tax-profit-margin and 5 other fieldsHigh correlation
gross-margin is highly correlated with pre-tax-profit-margin and 8 other fieldsHigh correlation
operating-margin is highly correlated with pre-tax-profit-margin and 5 other fieldsHigh correlation
roe is highly correlated with roa and 2 other fieldsHigh correlation
asset-turnover is highly correlated with receiveable-turnover and 2 other fieldsHigh correlation
roi is highly correlated with pre-tax-profit-margin and 6 other fieldsHigh correlation
days-sales-in-receivables is highly correlated with gross-margin and 1 other fieldsHigh correlation
book-value-per-share is highly correlated with gross-margin and 2 other fieldsHigh correlation
net-profit-margin is highly correlated with pre-tax-profit-margin and 6 other fieldsHigh correlation
return-on-tangible-equity is highly skewed (γ1 = 27.09442111) Skewed
sigma has unique values Unique

Reproduction

Analysis started2021-05-26 18:17:48.972080
Analysis finished2021-05-26 18:18:37.614275
Duration48.64 seconds
Software versionpandas-profiling v3.0.0
Download configurationconfig.json

Variables

current-ratio
Real number (ℝ≥0)

Distinct1056
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.836772593
Minimum0.6058
Maximum10.2911
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.6 KiB
2021-05-26T14:18:37.885422image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0.6058
5-th percentile0.78648
Q11.072825
median1.6114
Q32.165425
95-th percentile3.582115
Maximum10.2911
Range9.6853
Interquartile range (IQR)1.0926

Descriptive statistics

Standard deviation1.163278872
Coefficient of variation (CV)0.6333276511
Kurtosis11.97975226
Mean1.836772593
Median Absolute Deviation (MAD)0.54705
Skewness2.841235716
Sum1983.7144
Variance1.353217733
MonotonicityNot monotonic
2021-05-26T14:18:38.166674image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.11843
 
0.3%
1.07432
 
0.2%
1.83572
 
0.2%
1.00622
 
0.2%
1.17432
 
0.2%
0.75982
 
0.2%
1.10892
 
0.2%
0.96612
 
0.2%
1.56322
 
0.2%
1.21982
 
0.2%
Other values (1046)1059
98.1%
ValueCountFrequency (%)
0.60581
0.1%
0.62711
0.1%
0.63111
0.1%
0.63781
0.1%
0.6741
0.1%
0.6761
0.1%
0.67931
0.1%
0.681
0.1%
0.69191
0.1%
0.69261
0.1%
ValueCountFrequency (%)
10.29111
0.1%
8.98481
0.1%
8.64921
0.1%
8.54251
0.1%
8.42031
0.1%
8.25641
0.1%
8.25611
0.1%
8.02691
0.1%
7.94361
0.1%
7.81981
0.1%

gross-margin
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct997
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53.10515
Minimum-17.4856
Maximum129.3317
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)0.1%
Memory size8.6 KiB
2021-05-26T14:18:38.412015image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-17.4856
5-th percentile12.97307
Q131.8493
median50.35775
Q376.021275
95-th percentile100
Maximum129.3317
Range146.8173
Interquartile range (IQR)44.171975

Descriptive statistics

Standard deviation26.13756085
Coefficient of variation (CV)0.492185049
Kurtosis-0.8539319794
Mean53.10515
Median Absolute Deviation (MAD)19.8873
Skewness0.2109783888
Sum57353.562
Variance683.1720874
MonotonicityNot monotonic
2021-05-26T14:18:38.718066image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10082
 
7.6%
61.29092
 
0.2%
58.30932
 
0.2%
13.17871
 
0.1%
12.45751
 
0.1%
76.25991
 
0.1%
59.64431
 
0.1%
8.93471
 
0.1%
77.25871
 
0.1%
12.92471
 
0.1%
Other values (987)987
91.4%
ValueCountFrequency (%)
-17.48561
0.1%
1.70351
0.1%
4.51421
0.1%
6.3991
0.1%
7.78761
0.1%
7.84891
0.1%
8.21851
0.1%
8.22381
0.1%
8.41861
0.1%
8.59381
0.1%
ValueCountFrequency (%)
129.33171
 
0.1%
124.49021
 
0.1%
115.80791
 
0.1%
10082
7.6%
94.441
 
0.1%
94.30091
 
0.1%
94.27481
 
0.1%
94.0451
 
0.1%
93.99081
 
0.1%
93.62141
 
0.1%

operating-margin
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct1077
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.42385861
Minimum-398.3604
Maximum69.4912
Zeros0
Zeros (%)0.0%
Negative63
Negative (%)5.8%
Memory size8.6 KiB
2021-05-26T14:18:38.981362image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-398.3604
5-th percentile-1.052825
Q18.4466
median18.36625
Q329.366425
95-th percentile55.085415
Maximum69.4912
Range467.8516
Interquartile range (IQR)20.919825

Descriptive statistics

Standard deviation25.8700549
Coefficient of variation (CV)1.404160521
Kurtosis93.44618205
Mean18.42385861
Median Absolute Deviation (MAD)10.4468
Skewness-6.940098645
Sum19897.7673
Variance669.2597407
MonotonicityNot monotonic
2021-05-26T14:18:39.260617image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13.53452
 
0.2%
32.38642
 
0.2%
18.7742
 
0.2%
15.13651
 
0.1%
19.61491
 
0.1%
33.9531
 
0.1%
3.86751
 
0.1%
12.74041
 
0.1%
21.49111
 
0.1%
12.90761
 
0.1%
Other values (1067)1067
98.8%
ValueCountFrequency (%)
-398.36041
0.1%
-294.23871
0.1%
-216.46981
0.1%
-205.52631
0.1%
-111.81111
0.1%
-101.63741
0.1%
-100.97641
0.1%
-55.83181
0.1%
-36.59311
0.1%
-36.53681
0.1%
ValueCountFrequency (%)
69.49121
0.1%
68.42861
0.1%
67.59281
0.1%
67.50821
0.1%
67.2091
0.1%
67.12631
0.1%
67.03111
0.1%
66.91781
0.1%
66.91111
0.1%
66.33631
0.1%

ebit-margin
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct1077
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.52549602
Minimum-398.3604
Maximum69.4912
Zeros0
Zeros (%)0.0%
Negative63
Negative (%)5.8%
Memory size8.6 KiB
2021-05-26T14:18:39.502315image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-398.3604
5-th percentile-1.052825
Q18.702375
median18.3853
Q329.366425
95-th percentile55.085415
Maximum69.4912
Range467.8516
Interquartile range (IQR)20.66405

Descriptive statistics

Standard deviation25.84626911
Coefficient of variation (CV)1.395172852
Kurtosis93.91136154
Mean18.52549602
Median Absolute Deviation (MAD)10.21585
Skewness-6.970323235
Sum20007.5357
Variance668.0296271
MonotonicityNot monotonic
2021-05-26T14:18:39.746662image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.7742
 
0.2%
32.38642
 
0.2%
13.53452
 
0.2%
15.13651
 
0.1%
13.67391
 
0.1%
19.61491
 
0.1%
33.9531
 
0.1%
3.86751
 
0.1%
12.74041
 
0.1%
21.49111
 
0.1%
Other values (1067)1067
98.8%
ValueCountFrequency (%)
-398.36041
0.1%
-294.23871
0.1%
-216.46981
0.1%
-205.52631
0.1%
-111.81111
0.1%
-101.63741
0.1%
-100.97641
0.1%
-55.83181
0.1%
-36.59311
0.1%
-36.53681
0.1%
ValueCountFrequency (%)
69.49121
0.1%
68.42861
0.1%
67.59281
0.1%
67.50821
0.1%
67.2091
0.1%
67.12631
0.1%
67.03111
0.1%
66.91781
0.1%
66.91111
0.1%
66.33631
0.1%

pre-tax-profit-margin
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct1078
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.42620454
Minimum-395.8054
Maximum74.0253
Zeros0
Zeros (%)0.0%
Negative71
Negative (%)6.6%
Memory size8.6 KiB
2021-05-26T14:18:39.981472image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-395.8054
5-th percentile-5.84123
Q16.979825
median16.74215
Q328.793325
95-th percentile54.090035
Maximum74.0253
Range469.8307
Interquartile range (IQR)21.8135

Descriptive statistics

Standard deviation26.12481586
Coefficient of variation (CV)1.499168439
Kurtosis88.73654305
Mean17.42620454
Median Absolute Deviation (MAD)10.75155
Skewness-6.711399514
Sum18820.3009
Variance682.5060037
MonotonicityNot monotonic
2021-05-26T14:18:40.216842image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25.33712
 
0.2%
3.0952
 
0.2%
5.44381
 
0.1%
-13.79321
 
0.1%
15.01041
 
0.1%
31.98531
 
0.1%
12.67661
 
0.1%
19.41971
 
0.1%
37.10771
 
0.1%
16.62761
 
0.1%
Other values (1068)1068
98.9%
ValueCountFrequency (%)
-395.80541
0.1%
-297.72271
0.1%
-220.91651
0.1%
-206.66921
0.1%
-112.70251
0.1%
-101.63741
0.1%
-101.01941
0.1%
-54.16631
0.1%
-40.60611
0.1%
-39.24291
0.1%
ValueCountFrequency (%)
74.02531
0.1%
67.31941
0.1%
66.94051
0.1%
66.92761
0.1%
66.88351
0.1%
66.77881
0.1%
66.61871
0.1%
66.45131
0.1%
66.19861
0.1%
66.02221
0.1%

net-profit-margin
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct1079
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.69518537
Minimum-396.2143
Maximum65.7126
Zeros0
Zeros (%)0.0%
Negative83
Negative (%)7.7%
Memory size8.6 KiB
2021-05-26T14:18:40.464178image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-396.2143
5-th percentile-7.539355
Q14.88635
median12.18675
Q321.704725
95-th percentile40.403375
Maximum65.7126
Range461.9269
Interquartile range (IQR)16.818375

Descriptive statistics

Standard deviation24.08975056
Coefficient of variation (CV)1.897550123
Kurtosis116.8255271
Mean12.69518537
Median Absolute Deviation (MAD)8.3527
Skewness-8.294401742
Sum13710.8002
Variance580.3160821
MonotonicityNot monotonic
2021-05-26T14:18:40.699549image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.65652
 
0.2%
49.05931
 
0.1%
19.80981
 
0.1%
38.61661
 
0.1%
0.26731
 
0.1%
2.29921
 
0.1%
40.18891
 
0.1%
3.73751
 
0.1%
24.9951
 
0.1%
7.51771
 
0.1%
Other values (1069)1069
99.0%
ValueCountFrequency (%)
-396.21431
0.1%
-297.91831
0.1%
-221.1481
0.1%
-206.95621
0.1%
-112.85331
0.1%
-101.25841
0.1%
-73.84541
0.1%
-71.69591
0.1%
-41.82511
0.1%
-40.95241
0.1%
ValueCountFrequency (%)
65.71261
0.1%
60.85681
0.1%
54.98161
0.1%
54.96751
0.1%
54.90141
0.1%
54.4461
0.1%
54.18641
0.1%
54.06831
0.1%
54.04691
0.1%
53.09931
0.1%

asset-turnover
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct934
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2431631481
Minimum0.0038
Maximum1.1871
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.6 KiB
2021-05-26T14:18:40.927938image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0.0038
5-th percentile0.067175
Q10.122775
median0.17565
Q30.33245
95-th percentile0.610765
Maximum1.1871
Range1.1833
Interquartile range (IQR)0.209675

Descriptive statistics

Standard deviation0.1865749854
Coefficient of variation (CV)0.7672831463
Kurtosis4.116126573
Mean0.2431631481
Median Absolute Deviation (MAD)0.0822
Skewness1.795366983
Sum262.6162
Variance0.03481022517
MonotonicityNot monotonic
2021-05-26T14:18:41.143450image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.11335
 
0.5%
0.14764
 
0.4%
0.12274
 
0.4%
0.0093
 
0.3%
0.12623
 
0.3%
0.13563
 
0.3%
0.073
 
0.3%
0.06833
 
0.3%
0.15833
 
0.3%
0.12673
 
0.3%
Other values (924)1046
96.9%
ValueCountFrequency (%)
0.00381
0.1%
0.00661
0.1%
0.0071
0.1%
0.00721
0.1%
0.00731
0.1%
0.00782
0.2%
0.0081
0.1%
0.00831
0.1%
0.00841
0.1%
0.00872
0.2%
ValueCountFrequency (%)
1.18711
0.1%
1.16381
0.1%
1.10241
0.1%
1.08771
0.1%
1.08361
0.1%
1.07571
0.1%
1.07281
0.1%
1.0531
0.1%
1.04621
0.1%
0.96091
0.1%

receiveable-turnover
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct1067
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.223371296
Minimum0.0406
Maximum34.4406
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.6 KiB
2021-05-26T14:18:41.412671image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0.0406
5-th percentile1.148975
Q11.797225
median2.3834
Q33.571275
95-th percentile20.44938
Maximum34.4406
Range34.4
Interquartile range (IQR)1.77405

Descriptive statistics

Standard deviation5.521925982
Coefficient of variation (CV)1.307468748
Kurtosis8.425948528
Mean4.223371296
Median Absolute Deviation (MAD)0.71355
Skewness2.994576843
Sum4561.241
Variance30.49166656
MonotonicityNot monotonic
2021-05-26T14:18:41.657016image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.10112
 
0.2%
2.41792
 
0.2%
2.22532
 
0.2%
2.63252
 
0.2%
2.30862
 
0.2%
2.23242
 
0.2%
1.81372
 
0.2%
0.08122
 
0.2%
2.41472
 
0.2%
2.35782
 
0.2%
Other values (1057)1060
98.1%
ValueCountFrequency (%)
0.04061
0.1%
0.06711
0.1%
0.06881
0.1%
0.06931
0.1%
0.07231
0.1%
0.07631
0.1%
0.07651
0.1%
0.07731
0.1%
0.08122
0.2%
0.08141
0.1%
ValueCountFrequency (%)
34.44061
0.1%
31.40161
0.1%
30.94341
0.1%
30.94331
0.1%
29.53911
0.1%
29.23041
0.1%
29.20131
0.1%
29.21
0.1%
27.051
0.1%
26.95011
0.1%

days-sales-in-receivables
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct1077
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.70540713
Minimum2.6132
Maximum2216.78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.6 KiB
2021-05-26T14:18:41.905382image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum2.6132
5-th percentile4.4011
Q125.20105
median37.761
Q350.07805
95-th percentile78.33134
Maximum2216.78
Range2214.1668
Interquartile range (IQR)24.877

Descriptive statistics

Standard deviation187.7470797
Coefficient of variation (CV)2.618311327
Kurtosis35.34840922
Mean71.70540713
Median Absolute Deviation (MAD)12.48745
Skewness5.628976652
Sum77441.8397
Variance35248.96592
MonotonicityNot monotonic
2021-05-26T14:18:42.110855image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.90852
 
0.2%
4.60662
 
0.2%
38.98452
 
0.2%
58.67861
 
0.1%
47.38851
 
0.1%
29.20561
 
0.1%
27.52661
 
0.1%
22.30871
 
0.1%
30.44781
 
0.1%
55.29991
 
0.1%
Other values (1067)1067
98.8%
ValueCountFrequency (%)
2.61321
0.1%
2.86611
0.1%
2.90852
0.2%
3.04681
0.1%
3.0791
0.1%
3.08211
0.1%
3.08221
0.1%
3.32721
0.1%
3.33951
0.1%
3.35091
0.1%
ValueCountFrequency (%)
2216.781
0.1%
1341.4261
0.1%
1308.3611
0.1%
1298.6711
0.1%
1244.8161
0.1%
1179.0861
0.1%
1176.1051
0.1%
1163.8071
0.1%
1108.3471
0.1%
1107.9271
0.1%

roe
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct1077
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.339295833
Minimum-1058.823
Maximum1458.974
Zeros0
Zeros (%)0.0%
Negative106
Negative (%)9.8%
Memory size8.6 KiB
2021-05-26T14:18:42.305324image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-1058.823
5-th percentile-11.92594
Q13.294675
median5.85785
Q39.922975
95-th percentile35.17226
Maximum1458.974
Range2517.797
Interquartile range (IQR)6.6283

Descriptive statistics

Standard deviation70.23355324
Coefficient of variation (CV)9.56952204
Kurtosis267.00294
Mean7.339295833
Median Absolute Deviation (MAD)3.0203
Skewness1.750469819
Sum7926.4395
Variance4932.752
MonotonicityNot monotonic
2021-05-26T14:18:42.525738image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.8562
 
0.2%
3.34042
 
0.2%
5.91552
 
0.2%
4.68681
 
0.1%
10.50011
 
0.1%
8.15651
 
0.1%
2.90221
 
0.1%
9.4311
 
0.1%
25.64931
 
0.1%
11.17981
 
0.1%
Other values (1067)1067
98.8%
ValueCountFrequency (%)
-1058.8231
0.1%
-1042.3421
0.1%
-500.2991
0.1%
-194.65241
0.1%
-169.73871
0.1%
-105.45451
0.1%
-87.91821
0.1%
-78.52971
0.1%
-72.11951
0.1%
-69.73411
0.1%
ValueCountFrequency (%)
1458.9741
0.1%
397.50311
0.1%
250.32891
0.1%
242.79751
0.1%
208.21431
0.1%
170.76541
0.1%
147.0061
0.1%
128.36881
0.1%
123.77521
0.1%
108.63421
0.1%

return-on-tangible-equity
Real number (ℝ)

SKEWED

Distinct1079
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.61555926
Minimum-4503.571
Maximum19186.67
Zeros0
Zeros (%)0.0%
Negative358
Negative (%)33.1%
Memory size8.6 KiB
2021-05-26T14:18:42.756567image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-4503.571
5-th percentile-51.582105
Q1-6.714125
median6.1719
Q313.27035
95-th percentile53.782125
Maximum19186.67
Range23690.241
Interquartile range (IQR)19.984475

Descriptive statistics

Standard deviation618.4816593
Coefficient of variation (CV)39.60675689
Kurtosis861.1433446
Mean15.61555926
Median Absolute Deviation (MAD)10.10745
Skewness27.09442111
Sum16864.804
Variance382519.5629
MonotonicityNot monotonic
2021-05-26T14:18:42.965952image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.37732
 
0.2%
-51.891
 
0.1%
177.79161
 
0.1%
-3.28661
 
0.1%
24.78691
 
0.1%
15.41121
 
0.1%
7.40051
 
0.1%
133.37481
 
0.1%
-2.92311
 
0.1%
11.84371
 
0.1%
Other values (1069)1069
99.0%
ValueCountFrequency (%)
-4503.5711
0.1%
-3572.8811
0.1%
-1801.0641
0.1%
-840.78951
0.1%
-793.33331
0.1%
-514.70591
0.1%
-422.91671
0.1%
-392.18441
0.1%
-272.27931
0.1%
-271.98951
0.1%
ValueCountFrequency (%)
19186.671
0.1%
1243.2691
0.1%
796.31581
0.1%
734.05021
0.1%
679.08161
0.1%
545.37821
0.1%
542.85711
0.1%
468.93491
0.1%
438.41341
0.1%
426.12621
0.1%

roa
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct1074
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.289651389
Minimum-13.6934
Maximum19.8728
Zeros0
Zeros (%)0.0%
Negative83
Negative (%)7.7%
Memory size8.6 KiB
2021-05-26T14:18:43.172941image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-13.6934
5-th percentile-1.22071
Q11.204675
median2.28155
Q33.61785
95-th percentile5.80581
Maximum19.8728
Range33.5662
Interquartile range (IQR)2.413175

Descriptive statistics

Standard deviation2.586426598
Coefficient of variation (CV)1.129615893
Kurtosis9.838313678
Mean2.289651389
Median Absolute Deviation (MAD)1.2168
Skewness-1.234660762
Sum2472.8235
Variance6.689602546
MonotonicityNot monotonic
2021-05-26T14:18:43.418255image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.51652
 
0.2%
3.90882
 
0.2%
0.77972
 
0.2%
5.5242
 
0.2%
2.52722
 
0.2%
1.46482
 
0.2%
5.36121
 
0.1%
2.90231
 
0.1%
1.54791
 
0.1%
1.63151
 
0.1%
Other values (1064)1064
98.5%
ValueCountFrequency (%)
-13.69341
0.1%
-13.59341
0.1%
-11.82841
0.1%
-11.8251
0.1%
-11.80831
0.1%
-11.42191
0.1%
-11.22791
0.1%
-10.69841
0.1%
-9.66291
0.1%
-9.29351
0.1%
ValueCountFrequency (%)
19.87281
0.1%
12.15061
0.1%
10.85521
0.1%
9.95461
0.1%
9.42021
0.1%
9.26541
0.1%
9.00641
0.1%
8.54681
0.1%
8.52491
0.1%
8.28111
0.1%

roi
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct1076
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.869756481
Minimum-28.2224
Maximum28.8795
Zeros0
Zeros (%)0.0%
Negative83
Negative (%)7.7%
Memory size8.6 KiB
2021-05-26T14:18:43.662601image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-28.2224
5-th percentile-2.351885
Q12.0715
median3.86525
Q35.9301
95-th percentile10.50602
Maximum28.8795
Range57.1019
Interquartile range (IQR)3.8586

Descriptive statistics

Standard deviation4.584574927
Coefficient of variation (CV)1.184719232
Kurtosis9.26523692
Mean3.869756481
Median Absolute Deviation (MAD)1.9235
Skewness-1.271508624
Sum4179.337
Variance21.01832726
MonotonicityNot monotonic
2021-05-26T14:18:43.888995image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.31842
 
0.2%
1.72822
 
0.2%
2.82652
 
0.2%
2.61212
 
0.2%
3.53851
 
0.1%
0.32751
 
0.1%
8.65891
 
0.1%
8.02511
 
0.1%
4.65591
 
0.1%
4.85531
 
0.1%
Other values (1066)1066
98.7%
ValueCountFrequency (%)
-28.22241
0.1%
-22.85941
0.1%
-22.8041
0.1%
-21.31031
0.1%
-20.12891
0.1%
-18.36891
0.1%
-18.04981
0.1%
-16.77351
0.1%
-16.45551
0.1%
-16.38161
0.1%
ValueCountFrequency (%)
28.87951
0.1%
22.73441
0.1%
21.79191
0.1%
20.07571
0.1%
17.37411
0.1%
16.94421
0.1%
16.58541
0.1%
16.48151
0.1%
16.29481
0.1%
16.2521
0.1%

book-value-per-share
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION

Distinct1079
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.18046972
Minimum-12.7175
Maximum287.2318
Zeros0
Zeros (%)0.0%
Negative37
Negative (%)3.4%
Memory size8.6 KiB
2021-05-26T14:18:44.110407image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-12.7175
5-th percentile0.599345
Q16.086925
median11.538
Q322.0596
95-th percentile116.75221
Maximum287.2318
Range299.9493
Interquartile range (IQR)15.972675

Descriptive statistics

Standard deviation43.4579332
Coefficient of variation (CV)1.797232796
Kurtosis13.93263525
Mean24.18046972
Median Absolute Deviation (MAD)6.49525
Skewness3.655051625
Sum26114.9073
Variance1888.591958
MonotonicityNot monotonic
2021-05-26T14:18:44.338796image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24.05352
 
0.2%
7.73561
 
0.1%
0.2411
 
0.1%
12.46761
 
0.1%
9.21991
 
0.1%
4.68421
 
0.1%
3.38881
 
0.1%
2.73951
 
0.1%
1.6821
 
0.1%
22.02951
 
0.1%
Other values (1069)1069
99.0%
ValueCountFrequency (%)
-12.71751
0.1%
-12.49951
0.1%
-11.41841
0.1%
-11.41651
0.1%
-11.37041
0.1%
-11.00131
0.1%
-9.69781
0.1%
-8.9661
0.1%
-8.81131
0.1%
-8.58011
0.1%
ValueCountFrequency (%)
287.23181
0.1%
278.81
0.1%
269.27581
0.1%
268.65531
0.1%
261.76171
0.1%
259.87281
0.1%
257.36981
0.1%
252.09961
0.1%
246.12841
0.1%
245.23991
0.1%

sigma
Real number (ℝ≥0)

UNIQUE

Distinct1080
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01545417606
Minimum0.00059529
Maximum0.123591654
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.6 KiB
2021-05-26T14:18:44.551250image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0.00059529
5-th percentile0.0041437389
Q10.0074460325
median0.0121869245
Q30.01947309275
95-th percentile0.03732603275
Maximum0.123591654
Range0.122996364
Interquartile range (IQR)0.01202706025

Descriptive statistics

Standard deviation0.01224277033
Coefficient of variation (CV)0.7921981917
Kurtosis14.81865922
Mean0.01545417606
Median Absolute Deviation (MAD)0.0055702155
Skewness2.861845738
Sum16.69051015
Variance0.0001498854254
MonotonicityNot monotonic
2021-05-26T14:18:44.795594image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0048028291
 
0.1%
0.0047738111
 
0.1%
0.0178961781
 
0.1%
0.0209846241
 
0.1%
0.0120419311
 
0.1%
0.0122456561
 
0.1%
0.0085288171
 
0.1%
0.0104676291
 
0.1%
0.0093499141
 
0.1%
0.0101037481
 
0.1%
Other values (1070)1070
99.1%
ValueCountFrequency (%)
0.000595291
0.1%
0.0015724671
0.1%
0.0016205951
0.1%
0.0016835121
0.1%
0.0017853721
0.1%
0.001805681
0.1%
0.0018665541
0.1%
0.0019498671
0.1%
0.0020293941
0.1%
0.0021480741
0.1%
ValueCountFrequency (%)
0.1235916541
0.1%
0.1175217551
0.1%
0.0958490531
0.1%
0.0913635691
0.1%
0.0832936381
0.1%
0.0702014551
0.1%
0.0679562361
0.1%
0.0641923311
0.1%
0.0602728491
0.1%
0.0587435781
0.1%

Interactions

2021-05-26T14:17:54.547671image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:54.712199image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:54.877769image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:55.137281image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:55.291408image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:55.452946image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:55.600574image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:55.765112image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:55.921695image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:56.073320image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:56.222426image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:56.373993image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:56.546585image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:56.708633image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:56.866595image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:57.023175image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:57.186736image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:57.362240image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:57.526828image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:57.692390image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:57.854954image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:58.017516image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:58.195197image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:58.365250image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:58.533813image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:58.700386image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:58.868930image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:59.039448image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:59.205005image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:59.374616image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:59.544115image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:59.812258image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:17:59.975811image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:00.125392image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:00.277984image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:00.427584image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:00.584194image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:00.742742image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:00.915280image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:01.059923image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:01.215245image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:01.371820image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:01.530679image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:01.687739image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:01.842865image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:02.005404image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:02.152019image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:02.305601image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:02.458222image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:02.604828image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:02.749193image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:02.900297image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:03.057413image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:03.215019image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:03.367377image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:03.519689image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:03.678256image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:03.825893image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:03.982442image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:04.139059image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:04.290620image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:04.441247image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:04.597868image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:04.748502image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:04.901451image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:05.054773image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:05.359927image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:05.514540image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:05.676108image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:05.825682image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:05.980304image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:06.135853image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:06.293472image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:06.449084image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:06.607825image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:06.767472image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:06.914054image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:07.073657image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:07.219270image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:07.368882image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:07.530433image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:07.685427image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:07.838082image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:07.998626image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:08.148873image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:08.301867image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:08.455484image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:08.613069image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:08.767622image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:08.926228image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:09.091757image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:09.257344image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:09.424670image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:09.621130image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:09.814625image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:09.978270image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:10.183172image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:10.409566image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:10.646934image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:10.851384image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:11.054235image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:11.300566image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:11.542429image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:11.761844image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:11.994221image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:12.193688image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:12.416093image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:12.622540image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:13.088806image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:13.297252image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:13.561540image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:13.767990image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:13.972963image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:14.169049image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:14.379434image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:14.653212image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:14.850685image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:15.048155image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:15.249616image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:15.466038image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:15.678842image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:15.841704image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:16.078073image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:16.266081image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:16.447596image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:16.631105image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:16.896395image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:17.102864image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:17.311830image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:17.509914image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:17.689196image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:17.860608image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:18.065061image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:18.272507image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:18.466986image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:18.650497image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:18.927756image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:19.149670image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:19.345178image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:19.543648image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:19.742163image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:19.936655image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:20.125140image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:20.317135image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:20.507626image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:20.685495image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:20.849057image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:21.038552image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:21.207134image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:21.395597image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:21.583097image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:21.762394image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:21.983769image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:22.171931image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:22.333716image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:22.522218image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:22.700740image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:22.894263image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:23.092727image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:23.273210image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:23.797265image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:23.994730image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:24.184223image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:24.363778image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:24.534288image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:24.728797image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:24.917263image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:25.095818image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:25.257267image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:25.458737image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:25.643282image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:25.847698image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:26.054144image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:26.263584image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:26.457094image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:26.624106image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:26.828563image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:27.005607image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:27.216013image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:27.397556image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:27.567099image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:27.807435image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:28.015415image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:28.186764image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:28.353322image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:28.520282image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:28.691312image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:28.894283image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:29.063855image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:29.226421image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:29.404944image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:29.576485image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:29.752984image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:29.925530image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:30.108593image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:30.378434image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:30.529032image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:30.706585image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:30.910020image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:31.093553image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:31.298972image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:31.468800image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:31.634977image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:31.805521image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:31.970113image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:32.151611image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:32.339128image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:32.534572image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:32.711100image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:32.901615image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:33.078455image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:33.260236image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:33.481644image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:33.665153image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:33.883569image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:34.157356image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:34.341682image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:34.650084image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:34.856531image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:35.073950image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:35.274414image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:35.478867image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:36.010499image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:36.229720image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-05-26T14:18:36.441667image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Correlations

2021-05-26T14:18:45.006033image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-05-26T14:18:45.366070image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-05-26T14:18:45.744567image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-05-26T14:18:46.106939image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2021-05-26T14:18:36.854438image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
A simple visualization of nullity by column.
2021-05-26T14:18:37.383154image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

current-ratiogross-marginoperating-marginebit-marginpre-tax-profit-marginnet-profit-marginasset-turnoverreceiveable-turnoverdays-sales-in-receivablesroereturn-on-tangible-equityroaroibook-value-per-sharesigma
01.141742.506530.700830.700831.267926.37750.26572.711733.189434.158334.15837.008613.28874.14580.017064
11.163039.777830.091830.091830.132225.80340.31481.901047.342543.420843.42088.121617.37413.93650.016324
21.363638.160422.836922.836923.031619.58790.19981.727852.088919.395819.39583.91287.72723.84870.023187
31.469537.999521.933521.933522.010618.85400.18811.860848.366415.568215.56823.54606.76554.21820.033035
41.496038.361922.041422.041422.525019.29070.18201.900947.346714.343614.34363.51096.71544.53430.011731
51.597838.354827.847227.847228.227324.21720.26962.298639.154624.836124.83616.528112.17685.10440.033503
61.540137.965324.398824.398825.182721.37100.18921.398164.371615.124715.12474.04297.50765.09130.011626
71.504637.590421.453721.453722.135718.66600.16702.032544.280010.413010.41303.11695.53725.32150.027358
81.315437.612723.123323.123323.774919.92760.16962.207740.765710.921010.92103.38045.89665.74420.020733
91.300637.991927.690727.690728.354923.68050.22562.279839.476816.935016.93505.34229.46746.23130.015753

Last rows

current-ratiogross-marginoperating-marginebit-marginpre-tax-profit-marginnet-profit-marginasset-turnoverreceiveable-turnoverdays-sales-in-receivablesroereturn-on-tangible-equityroaroibook-value-per-sharesigma
10701.668035.66056.50246.50243.49083.28540.33841.673553.778211.0599-23.88061.11191.93700.60030.010815
10711.694039.5349-2.4978-2.4978-6.1154-6.37380.29791.732851.9380-20.612826.3345-1.8989-3.08200.49860.014160
10721.769940.9007-9.0074-9.0074-13.2353-13.41910.28651.686853.3548-35.180763.4783-3.8451-5.94950.58120.055561
10731.621315.4113-36.5368-36.5368-40.6061-40.95240.28881.833349.0909-87.9182426.1262-11.8250-18.36890.75460.018355
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